基于改进蚁群算法的医药冷链物流运输路径优化  

Transportation Route Optimization of Pharmaceutical Cold Chain Logistics Based on Improved ant Colony Algorithm

作　　者：陈鑫影[1] 朱子青 胡明捷 CHEN Xinying;ZHU Ziqing;HU Mingjie(School of Computer and Communication Engineering,Dalian Jiaotong University,Dalian 116028,China)

机构地区：[1]大连交通大学计算机与通信工程学院,辽宁大连116028

出　　处：《大连交通大学学报》2024年第1期26-32,共7页Journal of Dalian Jiaotong University

基　　金：辽宁省科技计划项目(1655706734383)。

摘　　要：为解决大多数模型中制冷成本未考虑预冷参数而导致总成本求解精度不佳的问题,在制冷成本中加入预冷参数,得到新的总成本模型。基于遗传算法与IACO算法,提出了IGACO算法,此算法改进了传统蚁群算法的启发式因子与信息素更新方式,在此基础上加入交叉操作和变异因子,扩大算法搜索范围,进一步避免陷入局部最优的情况。经过试验对比分析,验证了IGACO算法所得出的最优路线、总成本、运行时间、收敛速度在一定程度上都优于其他算法。In order to solve the problem of poor accuracy of total cost solution due to precooling parameters not considered in most models,the precooling parameters are added to the cooling cost to obtain a new total cost model.Based on the genetic algorithm and IACO algorithm,the IGACO algorithm is proposed.This algorithm improves the heuristic factor and pheromone update method of the traditional ant colony algorithm.Crossover operation and variation factor are added on this basis to expand the search range of the algorithm,and further the situation of falling into local optimum is avoided.After experiment comparative analysis,it is verified that the optimal route,total cost,running time and convergence speed derived from the IGACO algorithm are better than other comparative algorithms to some extent.

关 键 词：冷链物流 IGACO算法 预冷参数 单点交叉 变异算子 

分 类 号：F426.72[经济管理—产业经济] R95[医药卫生—药学] F252[自动化与计算机技术—控制理论与控制工程] TP18[自动化与计算机技术—控制科学与工程]